Recorded presentation

Avinash Patwardhan, MD, MS, Consultant, 5510 Whitfield Court, Fairfax, VA 22032, (703) 217-6917, swatianu6388@yahoo.com

Prediction is the bottom line for any research. Optimization or betterment of the outcomes for human needs may be and invariably is the a priori purpose for research but purpose and job is not one and the same thing. In behavioral research, the statement: “Inferential or predictive statistics is the science of what is not” provides not only for a profound truth but also for a profound folly into which many a scholar loses track and perspective. When making peace with negative of the negative as positive is the only choice it becomes far more critical to minimize the “error.” Social statistics has come a long way since Pearson and Fisher founded the discipline. However, sadly enough, though other similar fields such as military sciences and economics have started using non-linear dynamical systems model (chaos theory & fractal mathematics) as predictive tools almost routinely, the bulk of the research in public health is still based on parametric paradigm. It is time that the field awakes en mass to the need of this paradigm shift, instead of clinging to the comfort of old science attempting incremental linear improvements in methods, at huge low yield investments. Complex systems like human behavior seem chaotic and unpredictable (initial condition catch) but they are still deterministic. Systems models do much better than linear in reducing error. This non-technical paper traces the evolution and the philosophical underpinnings of both, the old and the new science, challenging scholars, policymakers and practitioners to embrace the new inevitable.

Learning Objectives: At the conclusion of the session, the participant (learner) in this session will be able to

• Recognize the founding principle behind the concept of prediction (error) in statistics
• Construct a broad perspective on disciples of systems and cybernetics
• Discuss or describe the salient features of linear and non-linear systems
• Define technical terms like systems, complexity, non-linear dynamical system, chaos, fractal mathematics, initial conditions
• Apply the new perspective in defining, developing or creating innovative tools/models in prediction science
• Prioritize funding distribution on research

Keywords: Behavioral Research, Policy/Policy Development

Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.

Recorded presentation